Network Forensics Server
FreeNot checkedEnables AI agents to analyze PCAP files for network forensics using Wireshark/tshark, providing high-performance packet inspection, filtering, and protocol anal
About
Enables AI agents to analyze PCAP files for network forensics using Wireshark/tshark, providing high-performance packet inspection, filtering, and protocol analysis through the Model Context Protocol.
README
A high-performance MCP Server for Network Forensics that enables AI agents to analyze PCAP files through the Model Context Protocol. Built with direct tshark integration for maximum speed.
Features
- High Performance: Direct tshark subprocess calls (not PyShark) for 26-90x faster analysis
- Deep Packet Inspection: Access to all Wireshark dissectors (1000+ protocols)
- Advanced Filtering: Support for all Wireshark display filters
- Protocol Analysis: Automatic statistics and distribution analysis
- Security First: Path validation, size limits, input sanitization
- Memory Efficient: Streaming processing for large files (tested with 1M+ packets)
- Auto-Detection: Automatically finds tshark installation
Performance Benchmarks
Tested on a 1.1GB PCAP file with 1,028,287 packets:
| Operation | Time | Optimization |
|---|---|---|
| Packet Count | 0.6s | capinfos (26x faster) |
| Get Summary | 0.2s | -c flag (90x faster) |
| Filter HTTP | 13s | Full file scan |
| Protocol Stats | 17s | Full file scan |
| Extract IPs | 11s | Full file scan |
Requirements
- Python 3.9+
- Wireshark/tshark (4.0+) and capinfos installed
- MCP-compatible client (Claude Desktop, VSCode, Cline, etc.)
Installation
1. Install Wireshark
Ubuntu/Debian:
sudo apt-get update
sudo apt-get install tshark wireshark-common
macOS:
brew install wireshark
Windows: Download from wireshark.org
Verify installation:
tshark --version
capinfos --version # Optional, for faster packet counting
2. Install MCP Server
# Clone repository
git clone https://github.com/yourusername/mcp-network-forensics.git
cd mcp-network-forensics
# Create virtual environment
python -m venv venv
source venv/bin/activate # Linux/Mac
# or: venv\Scripts\activate # Windows
# Install package
pip install -e .
Configuration
Claude Desktop
Edit claude_desktop_config.json:
macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%/Claude/claude_desktop_config.json
{
"mcpServers": {
"network-forensics": {
"command": "python",
"args": ["-m", "mcp_network_forensics"],
"env": {
"MCP_MAX_FILE_SIZE": "10737418240",
"MCP_MAX_PACKETS": "10000",
"TSHARK_PATH": "/usr/bin/tshark"
}
}
}
}
VSCode (with Cline extension)
Add to your settings:
{
"mcpServers": {
"network-forensics": {
"command": "python",
"args": ["-m", "mcp_network_forensics"],
"disabled": false,
"autoApprove": []
}
}
}
Available Tools
1. analyze_pcap_file
Analyze a PCAP file and return summary statistics.
Parameters:
file_path: Absolute path to PCAP file (required)packet_limit: Maximum packets to analyze (default: 1000)display_filter: Optional Wireshark display filter
Example:
{
"file_path": "/home/user/captures/traffic.pcap",
"packet_limit": 100,
"display_filter": "ip.addr == 192.168.1.1"
}
2. get_packet_details
Get detailed information about a specific packet.
Parameters:
file_path: Absolute path to PCAP filepacket_index: Index of packet (0-based)include_layers: Include layer information (default: true)
Example:
{
"file_path": "/home/user/captures/traffic.pcap",
"packet_index": 0,
"include_layers": true
}
3. filter_packets
Filter packets using Wireshark display filter syntax.
Parameters:
file_path: Absolute path to PCAP filedisplay_filter: Wireshark filter (e.g., "tcp.port == 80", "http", "dns.qry.name contains 'google'")max_results: Maximum results to return (default: 100)
Example:
{
"file_path": "/home/user/captures/traffic.pcap",
"display_filter": "tcp.flags.syn == 1 and tcp.flags.ack == 0",
"max_results": 50
}
4. get_protocol_statistics
Get protocol distribution statistics.
Parameters:
file_path: Absolute path to PCAP filepacket_limit: Maximum packets to analyze (default: 1000)
Example:
{
"file_path": "/home/user/captures/traffic.pcap",
"packet_limit": 1000
}
5. extract_unique_ips
Extract unique IP addresses from the capture.
Parameters:
file_path: Absolute path to PCAP file
Example:
{
"file_path": "/home/user/captures/traffic.pcap"
}
Usage Examples
Basic Analysis
Please analyze this PCAP file and show me the protocol distribution.
File: /home/user/captures/traffic.pcap
Threat Hunting
Find all HTTP requests to external IPs in this capture.
File: /home/user/captures/web.pcap
Network Troubleshooting
Show me all TCP SYN packets without ACK (possible port scan).
File: /home/user/captures/suspicious.pcap
Deep Inspection
Get detailed information about packet 100, including all layers.
File: /home/user/captures/malware.pcap
Security Features
- Path Validation: Only absolute paths allowed, no directory traversal
- File Size Limits: Configurable max file size (default: 10GB)
- Packet Limits: Configurable max packets per request (default: 10,000)
- Filter Sanitization: Display filter validation and dangerous character detection
- Timeout Protection: Request timeout configuration (default: 300s)
Environment Variables
| Variable | Description | Default |
|---|---|---|
MCP_SERVER_NAME |
Server name | mcp-network-forensics |
MCP_MAX_FILE_SIZE |
Max file size in bytes | 10737418240 (10GB) |
MCP_MAX_PACKETS |
Max packets per request | 10000 |
MCP_TIMEOUT |
Request timeout in seconds | 300 |
TSHARK_PATH |
Path to tshark binary | auto-detect |
Architecture
┌─────────────────┐ ┌──────────────────┐ ┌─────────────┐
│ MCP Client │────▶│ MCP Server │────▶│ tshark │
│ (Claude/VSCode) │ │ (Python/FastMCP)│ │ (Wireshark)│
└─────────────────┘ └──────────────────┘ └─────────────┘
│
▼
┌──────────────┐
│ PCAP File │
└──────────────┘
Project Structure
mcp-network-forensics/
├── src/
│ └── mcp_network_forensics/
│ ├── __init__.py
│ ├── __main__.py # Entry point
│ ├── server.py # MCP server with tools
│ ├── config.py # Configuration
│ ├── exceptions.py # Custom exceptions
│ ├── capture/
│ │ ├── __init__.py
│ │ ├── file_capture.py # File capture manager
│ │ └── tshark_wrapper.py # Direct tshark integration
│ ├── models/
│ │ ├── __init__.py
│ │ └── packet.py # Pydantic models
│ └── utils/
│ ├── __init__.py
│ ├── validators.py # Input validation
│ └── formatters.py # Output formatting
├── pyproject.toml
├── requirements.txt
├── requirements-dev.txt
└── README.md
Development
Setup Development Environment
pip install -e ".[dev]"
Code Quality
black src
isort src
flake8 src
mypy src
Troubleshooting
tshark not found
# Check installation
which tshark # Linux/Mac
where tshark # Windows
# Set path manually
export TSHARK_PATH=/usr/bin/tshark # Linux/Mac
set TSHARK_PATH=C:\Program Files\Wireshark\tshark.exe # Windows
Timeout errors on large files
Increase timeout or reduce packet_limit:
export MCP_TIMEOUT=600
export MCP_MAX_PACKETS=5000
License
MIT License - see LICENSE file for details.
Acknowledgments
- Wireshark - Network protocol analyzer
- Model Context Protocol - MCP specification
- FastMCP - Python MCP SDK
Support
For issues and feature requests, please use the GitHub issue tracker.
Installing Network Forensics Server
This server has no published package — it is built from source. Open the repository and follow its README.
▸ github.com/jus1-c/network-forensics-mcp-serverFAQ
Is Network Forensics Server MCP free?
Yes, Network Forensics Server MCP is free — one-click install via Unyly at no cost.
Does Network Forensics Server need an API key?
No, Network Forensics Server runs without API keys or environment variables.
Is Network Forensics Server hosted or self-hosted?
Self-hosted: the server runs locally on your machine via the install command above.
How do I install Network Forensics Server in Claude Desktop, Claude Code or Cursor?
Open Network Forensics Server on unyly.org, pick your client tab (Claude Desktop, Claude Code, Cursor) and press Install — the config is generated automatically, no JSON editing.
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